The AI for Accelerated Materials Discovery (AI4Mat) Workshop NeurIPS 2024 provides an inclusive and collaborative platform where AI researchers and material scientists converge to tackle the cutting-edge challenges in AI-driven materials discovery and development. By taking a comprehensive look at automated materials discovery spanning AI-guided design, synthesis and automated material characterization, we hope to create an opportunity for deep, thoughtful discussion among researchers working on these interdisciplinary topics, and highlight ongoing challenges in the field. This year, AI4Mat will focus on two major themes:

Why Isn't it Real Yet? This discussion centers on why AI in materials science has not yet experienced the type of exponential growth seen in adjacent fields at the intersection of science and AI, such as large language models (LLM), multi-modal AI, drug discovery and computational biology.

AI4Mat Unique Challenges: Managing Multimodal, Incomplete Materials Data: A unique challenge in materials science is managing multimodal, incomplete data that is collected from diverse types of real-world equipment, including synthesis and characterization tools. Additionally, datasets and scientific understanding are often incomplete given the fact that fundamental physics and chemistry phenomena are sometimes unknown.